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---
title: Sparse Panel Demo
emoji: 🌫️
colorFrom: blue
colorTo: gray
sdk: gradio
sdk_version: 6.30.0
python_version: "3.12"
app_file: app.py
pinned: false
license: cc-by-4.0
short_description: Recovering smooth levels from sparse, gappy air-quality data
datasets:
  - prteek/sparse-panel-demo
---
Interactive companion to the blog post [Smooth Levels from Sparse, Gappy Panels](https://huggingface.co/blog/prteek/sparse-panel-modelling) on Hugging Face. Pick how many readings are kept and a group of stations, and compare a joint network, single-target networks and a ±15-day mean against the true 31-day level.

Code: [github.com/prteek/sparse-panel-modelling](https://github.com/prteek/sparse-panel-modelling) · Data: [prteek/sparse-panel-demo](https://huggingface.co/datasets/prteek/sparse-panel-demo), derived from the UCI Beijing Multi-Site Air Quality dataset (CC BY 4.0).

	---
	title: Sparse Panel Demo
	emoji: 🌫️
	colorFrom: blue
	colorTo: gray
	sdk: gradio
	sdk_version: 6.30.0
	python_version: "3.12"
	app_file: app.py
	pinned: false
	license: cc-by-4.0
	short_description: Recovering smooth levels from sparse, gappy air-quality data
	datasets:
	- prteek/sparse-panel-demo
	---

	Interactive companion to the blog post [Smooth Levels from Sparse, Gappy Panels](https://huggingface.co/blog/prteek/sparse-panel-modelling) on Hugging Face. Pick how many readings are kept and a group of stations, and compare a joint network, single-target networks and a ±15-day mean against the true 31-day level.

	Code: [github.com/prteek/sparse-panel-modelling](https://github.com/prteek/sparse-panel-modelling) · Data: [prteek/sparse-panel-demo](https://huggingface.co/datasets/prteek/sparse-panel-demo), derived from the UCI Beijing Multi-Site Air Quality dataset (CC BY 4.0).